1. Field of the Invention
This invention is generally related to the field of electronic recruiting and candidate matching and, more specifically, to systems and methods for processing natural language expressions of job specifications and candidate resumes.
2. Description of the Prior Art
Finding the right person at the right time in the right location to fill an open position is a major challenge for most companies because the process of recruiting new employees is inefficient, time-consuming, and costly. The same is true from a candidates perspective as finding the right job at the right time is also a significant challenge for most candidates because the process of matching a candidate's unique set of skills is inefficient, time consuming and costly. The proliferation of web-based technology for recruiting and matching has expanded employers' and job seekers' ability to find each other, but it has made the process of recruiting and matching increasingly complicated. Companies focus on recruiting people to fill positions, but they do not know whether the people they need exist in the locale where they are trying to hire. Job seekers focus on finding the right position, but they don't have a complete understanding of which specific skills companies value most.
In recent years the number of technology companies attempting to solve issues in the recruiting process has grown tremendously. The proliferation of web-based technologies includes a wide range of applicant tracking systems, data extraction methods, new search technologies, and processes to match the appropriate job seekers with open positions. Applicant tracking systems collect job description and job seeker (resume) information, but they do not have precise matching between the required elements of the job specification and the skills and experience of the job seeker.
Data extraction methods are based on individual words which do not capture nuances in various types of skills and experiences. Extraction also relies upon large databases of verified data. Most extraction technology providers do not have adequate databases of verified data or high quality validation.
Existing search and matching technologies mostly rely on key words linked with Boolean operators to launch searches and retrieve search results, but using keyword based searches does not provide precise matching results. The key words can be taken out of context and result in poor search matches. For example, for the phrase “design simulation,” existing technologies look for “design” and “simulation” as separate results and bring back results that are not relevant to the whole phrase “design simulation.”
There are a number of recruitment industry technology companies attempting to automate the matching process. Their technology, generally known as an applicant tracking system (ATS), also uses key word searching with Boolean operators to execute their matching process. ATS providers include Kenexa, Kronos, and Vurv among others.
Online job boards all provide search capabilities to perform matching, but they are also using key words with Boolean operators which result in imprecise matches. There are hundreds of online job boards, but some of the more well-known boards include Monster, CareerBuilder, TheLadders, and DICE.